Business enterprises may use large amounts of computational resources to support business operations. These computational resources may include processing time on central processing units to perform a plurality of calculations, or memory storage space, among others. In some instances, business enterprises may employ the services of a third-party to provide computational resource products, such as “cloud-based storage” services, and the like. In other instances a business enterprise may integrate the operation and maintenance of part or all of the computational resources used in support of business operations without employing the services of a third-party vendor. For example, a financial services company may operate and maintain tens, hundreds, or thousands of server computers in order to meet demands for storage and computational resources associated with the operations of the company. In some scenarios, such as those scenarios involving small and medium-sized enterprises (SMEs), these computational resources may be co-located, for example in a same server room, or a same office building, or spread out between multiple locations within a single geographic region, or country. In other scenarios, such as, for example, those related to multinational corporations (MNCs), computational resources may be distributed across multiple locations throughout the globe.
A business, such as an SME, MNC, or other size of business, may operate and maintain computational hardware to deliver computational resources to meet expected peak computational demands for a given location. For example, a given office of a financial services company may operate one or more on-site “server rooms” housing a plurality of server computers capable of providing computational resources to meet peak computational demands for the given office location. Furthermore, a business may operate additional computational hardware for redundancy, thereby maintaining computational capacity in times of partial failure of primary computational hardware. Accordingly, a business may operate and maintain computational hardware such that in order to meet peak computational demands, a portion of the total computational hardware lies idle during periods of average demand. This scenario may be associated with one or more locations of a business enterprise across a single geographic region, a country, or across multiple countries throughout the globe, and such that a business enterprise operates and maintains computational hardware and associated firmware and software services in excess of those computational demands received by the business enterprise on average.
Furthermore, certain events may be unexpected by business enterprises such that computational resources cannot meet demands. These events may be internal, such as, among others, a business decision to provide a new type of product, and the like. In other instances, these events may be external, such as, among others, a sudden rise in purchases from the company, unexpected adverse weather conditions affecting supply of a product to a geographic region, or an unexpected change in one or more financial markets around the world, among many others. Associated with each of these internal and external events may be a large increase, in demand for computational resources at one or more locations of a business enterprise, and wherein a given location of the business enterprise is unable to meet this increased demand for computational resources. However, in some instances, a business enterprise as a whole may comprise computational resources sufficient to meet an unexpected increase in demand, but is unable to redistribute computational tasks from one location to another due to, among others, incompatibility between computational resources at an origin location and an intended destination location, insufficient time for preparation to receive computational tasks at one or more locations in addition to an origin location experiencing increased demand, and/or impracticality associated with communicating large amounts of data to different locations in order to redistribute the computational tasks, among others.
Therefore, a need exists for improved systems and methods for distribution of computational tasks amongst separated computational resources of a business enterprise.